Senior Database and Platform Engineer

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Position Summary The Senior Database & Data Platform Engineer provides technical leadership for the design, administration, optimization, governance, and modernization of the organizations enterprise data platforms.

This role encompasses Microsoft SQL Server, Azure data services, Databricks Lakehouse, Microsoft Copilot, Azure AI Foundry, Claude, and other approved AI technologies.

The Engineer serves as a technical authority and operational owner, advancing secure and scalable data platforms that enable enterprise analytics, reporting, AI adoption, and digital modernization.

The role partners across technology and business teams to strengthen platform reliability, governance, innovation, and the effective use of enterprise data and AI capabilities.

Responsibilities Design and maintain enterprise data platform architecture supporting operational, analytics, and AI workloads.Develop modernization roadmaps for legacy database and data platforms while maintaining business continuity.Establish standards for database design, performance, security, availability, scalability, governance, and documentation.Evaluate emerging data and AI technologies and recommend future-state platform capabilities.Administer, optimize, and secure Microsoft SQL Server environments, including performance, backup/recovery, patching, upgrades, capacity, and disaster recovery.Lead disaster recovery testing, failover validation, production incident response, root cause analysis, and remediation.Manage platform reliability, observability, utilization, capacity, and cloud cost optimization.Provide technical ownership for Databricks, including Lakehouse architecture, Unity Catalog, workspace governance, compute, jobs, security, and optimization.Support analytics, reporting, machine learning, and AI initiatives through governed, trusted enterprise data.Define and support standards for data ingestion, transformation, orchestration, integration, ETL/ELT, and data movement.Oversee integrations across business systems, cloud services, SQL platforms, analytics environments, and AI services.Plan and execute data migrations, including validation, cutover, rollback, and transition activities.Establish data governance practices covering classification, retention, lineage, quality, stewardship, metadata, access, and audit readiness.Partner with business, security, legal, and technology stakeholders to strengthen d...